Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem
A swarm intelligence optimization algorithm called white shark optimizer (WSO) has been proposed and successfully applied in regard to many aspects. In this paper, the location problem of sports facilities is regarded as a multi-objective problem, and the number of residents covered by sports facilities and the Weber problem are introduced as objective functions. A multi-objective white shark optimizer (MOWSO) is proposed, and MOWSO introduced an archived mechanism to store the non-dominated solutions obtained by the algorithm. When the Pareto solutions in the archive overflow, the solutions are removed by calculating the true distance of the Pareto optimal solution. The performance of the MOWSO is verified on CEC 2020 benchmark functions, and the results show that the proposed MOWSO is better than other algorithms in the diversity and distribution of solutions. The MOWSO is applied to solve the rural sports facilities location problem, and a variety of different sports facilities location schemes are obtained. It can provide a variety of options for the location of rural sports facilities, and promote the intelligent design of sports facilities.
Authors
- Yongquan Zhou (ORCID: https://orcid.org/0000-0003-4404-952X)
- Bin Guo (ORCID: https://orcid.org/0000-0002-7093-2677)
- Yan Zheng
Institutions
- Minzu University of China (CN)
- China University of Political Science and Law (CN)
Publication Details
- Journal
- Biomimetics
- Published
- 2025-08-15
- DOI
- https://doi.org/10.3390/biomimetics10080537
- Primary Topic
- Urban Transport and Accessibility
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China